Understanding Gardar Sahlberg with neural nets : On algorithmic reuse of the Swedish SF archive

• In this article, we re-trace the history of the Swedish SF archive and reflect on how this collection of historic newsreels has been reappropriated and remixed through-out more recent media history. In particular, we focus on the work of director and film historian Gardar Sahlberg, who made extensive use of the SF archive, first in a series of documentary films, then in a number of historical TV programmes. We are interested in how historic film footage travels and circulates through time, but foremost we explore how algorithms can help identify instances of audio-visual reuse in large datasets. Hence the article discusses algorithmic ways of examining archival film reuse, introducing a method for mapping video reuse with the help of artificial intelligence or more precisely machine learning that uses so-called convo-lutional neural nets. The article presents the Video Reuse Detector (VRD), a tool that uses machine learning to identify visual similarities within a given audiovisual database such as the SF archive.

Ämnesord

HUMANIORA  -- Konst -- Filmvetenskap (hsv//swe)

HUMANITIES  -- Arts -- Studies on Film (hsv//eng)

Nyckelord

AI

archival reuse

computational film studies

convolutional neural nets

film archives

Video Reuse Detector

Publikations- och innehållstyp

ref (ämneskategori)

art (ämneskategori)